Segmentation of natural images for CBIR
P.S. Williams, Michael D. Alder · 2002
Examines the problem of segmenting colour images into homogeneous regions for use in content based image retrieval (CBIR) or object recognition in general. Low level features provide intensity, colour and texture characteristics across the entire image. From these feature vectors a measure of local homogeneity is obtained. Through iterative modelling a seed and grow style algorithm is used to locate each segment. The final segment models provide sufficient information for higher level processing or classification. Segmentation and classification results are illustrated from a database of 1000 Corel Photo CD images.